Wearable speech enhancement system based on MEMS microphone array for disabled people

Disabled people, especially the ones with motor skill impairments, have difficulties in interacting with personal computers and smartphones. Indeed Automatic Speech Recognition (ASR) could be helpful for those people, but it´s limited in scenarios not affected by environmental noise that can decrease performance of the recognition, limiting user experience. We propose a speech enhancement system based on MEMS microphone array and a digital signal processor in order to increase signal-to-noise ratio (SNR) of the user´s voice. The audio delay between microphones is exploited by the array using the Differential Microphone Array (DMA) and an Adaptive Noise Reduction techniques. In such way the system can obtain an increment in SNR about 16.5 dB, when noise and voice come from opposite directions. A voice activity detection (VAD) block recognizes when the user speaks and sends the data to a cloud-based ASR system. Due to the small array size, the embedded system can be integrated in a wearable device. Theoretical analysis and in-system measurements prove the effectiveness of the proposed solution.